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Background Mycobacterium chimera (MC) is a nontuberculous mycobacterium associated with infections originating from heater-cooler devices following cardiac surgery globally from 2012 to 2016. Twenty-eight cases occurred within our health system in Southern California, the largest number of cases in the United States to date. We aim to summarize the clinical features, diagnosis, treatments, and outcomes of these cases. Methods We reviewed the electronic health records of 28 patients with identified MC infection who had index coronary artery bypass (CABG) and/or valve replacement surgery between 2014 and 2016. All diagnoses were confirmed by cultures speciated to MC by 16S partial DNA sequencing or Karius testing, except for one case. Patients were grouped by clinical presentation of disseminated disease (n = 18) or localized disease (n = 10). Treatment delay was calculated from the time of initial presentation to the start date of antibiotics and evaluation for surgical intervention. Results All patients who underwent CABG alone (n = 5) developed localized sternal wound infections, whereas patients who had valve replacement surgery (n = 23) developed either localized or disseminated disease. Disseminated disease carried a mortality rate of 40% in those with surgical source control vs. 72% in patients who were not surgical candidates (OR 6.6, 95% CI 0.8–55). The mortality rate of patients with localized sternal wound infections was 11% after incision/drainage and sternal wire removal (n = 9). Delay of antimicrobial treatment greater than 6 months in all 28 patients was associated with a mortality rate of 54% compared with 35% in patients who started treatment within 6 months (OR 2.2, 95% CI 0.47–10.35). Overall mortality rate of patients with MC infection was 42%. Conclusion Disseminated MC infection should be considered early in at-risk patients presenting with constitutional symptoms. In this review of 27 confirmed and 1 probable case of MC infection, disseminated infection only occurred in patients who underwent valve surgery while localized disease occurred in patients who underwent CABG. Surgical source control with early initiation of antimicrobial therapy is associated with improved outcomes. Optimal duration of antimicrobial treatment is still unknown. Disclosures All authors: No reported disclosures. [ABSTRACT FROM AUTHOR]

In the United States the Heartmate3 (HM3) has become the only durable LVAD for implantation in end stage heart failure (HF) patients. Prior predictive scores included older generation devices and thus may not applicable. The purpose of this study was to develop a one-year survival predictive score for HM3 candidates. Adult patients registered in the STS-INTERMACS database, who received primary implant with a HM3 device between 1/1/2014 and 6/1/2020 were included in this study. Epidemiological, clinical, hemodynamic, and echocardiographic characteristics were analyzed. Machine learning, elastic-net method, was used to build a one-year mortality predictive model on the derivation cohort; and its performance was tested on the validation cohort. A total of 3642 patients met inclusion criteria. Of these, 429 died within 1 year after HM3 implantation. Non-survivors were older (61.7 vs. 56.8 years, p<0.001), less frequently male (15.2% vs. 20.6%, p=0.01), had higher frequency of chronic HF (82.8% vs. 79% p=0.004), had a higher frequency of ECMO (10.3 %vs. 4.26%, p<0.001), higher rates of dialysis (6.29% vs. 1.93%, p<0.001), higher frequency of previous cardiac surgery (35% vs. 24.2%, p<0.001), and higher frequency of concomitant cardiac surgery (50.4% vs. 44.3%, p =0.02). Machine learning identified 9 variables associated with one-year mortality in the training data set (Age, right atrial pressure, MELD-XI score, INTERMACS profile 1, Chronic HF, White blood cell count, hemoglobin, heart rate < 90, and ECMO prior to implant), with an AUC 0.68 (figure 1A). The importance of each variable in the predicting model is shown in figure 1B. Our score predicted one year survival in the testing cohort with a good accuracy (AUC:0.72, Figure 1C). Using the machine learning algorithm, we developed a model for predicting one-year survival for patients receiving HM3 LVAD. Age, right atrial pressure and MELD-XI score were the most important predictive factors. [ABSTRACT FROM AUTHOR]

Objective: Our study aimed to assess the heart failure/cardiomyopathy-related population-level mortality trends among patients with obesity in the United States and disparities across demographics., Methods: We queried the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research database among adults aged ≥25 from 1999 to 2019. Heart failure/cardiomyopathy were listed as the main causes of death, with obesity as a contributing cause. We calculated age-adjusted mortality rates (AAMR) per 100,000 individuals and estimated the average annual percent change (AAPC). We also evaluated the social vulnerability of United States counties (2014-2018)., Results: There were 29,334 deaths related to heart failure/cardiomyopathy among patients with comorbid obesity. The overall AAMR increased from 0.41 in 1999 to 0.94 in 2019, with an AAPC of 3.78 (95 % CI, 3.41-4.14). The crude mortality rate increase for heart failure/cardiomyopathy was greater in individuals with comorbid obesity than in those without. Males had a higher AAMR than females (0.78 vs 0.55). African Americans also had higher AAMR than Whites (1.35 vs 0.62). The AAMR was higher in rural areas than in urban regions (0.76 vs 0.66). The overall AAMR was higher in counties with social vulnerability index-Quartile 4 (SVI-Q4) (most vulnerable) (1.08) compared to SVI-Q1 (least vulnerable) (0.63) with a risk ratio of 1.71 (95 % CI: 1.61-1.83)., Conclusion: Heart failure/cardiomyopathy mortality in individuals with comorbid obesity was rising. Males, African Americans, and individuals from rural regions had higher AAMR than their counterparts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

HeartMate 3 is the only durable left ventricular assist devices (LVAD) currently implanted in the United States. The purpose of this study was to develop a predictive model for 1 year mortality of HeartMate 3 implanted patients, comparing standard statistical techniques and machine learning algorithms. Adult patients registered in the Society of Thoracic Surgeons, Interagency Registry for Mechanically Assisted Circulatory Support (STS-INTERMACS) database, who received primary implant with a HeartMate 3 between January 1, 2017, and December 31, 2019, were included. Epidemiological, clinical, hemodynamic, and echocardiographic characteristics were analyzed. Standard logistic regression and machine learning (elastic net and neural network) were used to predict 1 year survival. A total of 3,853 patients were included. Of these, 493 (12.8%) died within 1 year after implantation. Standard logistic regression identified age, Model End Stage Liver Disease (MELD)-XI score, right arterial (RA) pressure, INTERMACS profile, heart rate, and etiology of heart failure (HF), as important predictor factors for 1 year mortality with an area under the curve (AUC): 0.72 (0.66-0.77). This predictive model was noninferior to the ones developed using the elastic net or neural network. Standard statistical techniques were noninferior to neural networks and elastic net in predicting 1 year survival after HeartMate 3 implantation. The benefit of using machine-learning algorithms in the prediction of outcomes may depend on the type of dataset used for analysis., Competing Interests: M.L. discloses grants and consulting fees for Abbott and Abiomed. S.L. discloses support from Abbott to attend the Heart Failure User’s meetings in May 2022 and October 2019. R.Y.L.-R. discloses support from Abbott to attend an educational meeting in August 2023. The other authors have no conflicts of interest to report., (Copyright © ASAIO 2023.)

Background: The opioid epidemic in North America has been driven by an increase in the use and potency of prescription opioids, with ensuing excessive opioid-related deaths. Internationally, there are lower rates of opioid-related mortality, possibly because of differences in prescribing and health system policies. Our aim was to compare opioid prescribing rates in patients without cancer, across 5 centers in 4 countries. In addition, we evaluated differences in the type, strength, and starting dose of medication and whether these characteristics changed over time., Methods and Findings: We conducted a retrospective multicenter cohort study of adults who are new users of opioids without prior cancer. Electronic health records and administrative health records from Boston (United States), Quebec and Alberta (Canada), United Kingdom, and Taiwan were used to identify patients between 2006 and 2015. Standard dosages in morphine milligram equivalents (MMEs) were calculated according to The Centers for Disease Control and Prevention. Age- and sex-standardized opioid prescribing rates were calculated for each jurisdiction. Of the 2,542,890 patients included, 44,690 were from Boston (US), 1,420,136 Alberta, 26,871 Quebec (Canada), 1,012,939 UK, and 38,254 Taiwan. The highest standardized opioid prescribing rates in 2014 were observed in Alberta at 66/1,000 persons compared to 52, 51, and 18/1,000 in the UK, US, and Quebec, respectively. The median MME/day (IQR) at initiation was highest in Boston at 38 (20 to 45); followed by Quebec, 27 (18 to 43); Alberta, 23 (9 to 38); UK, 12 (7 to 20); and Taiwan, 8 (4 to 11). Oxycodone was the first prescribed opioid in 65% of patients in the US cohort compared to 14% in Quebec, 4% in Alberta, 0.1% in the UK, and none in Taiwan. One of the limitations was that data were not available from all centers for the entirety of the 10-year period., Conclusions: In this study, we observed substantial differences in opioid prescribing practices for non-cancer pain between jurisdictions. The preference to start patients on higher MME/day and more potent opioids in North America may be a contributing cause to the opioid epidemic., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: MJ is a member of the MHRA Opioids Expert Working Group. DB outlines the following disclosures, none directly relevant to this publication. He consults for EarlySense, which makes patient safety monitoring systems. He receives cash compensation from CDI (Negev), Ltd, which is a not-for-profit incubator for health IT startups. He receives equity from ValeraHealth which makes software to help patients with chronic diseases. He receives equity from Clew which makes software to support clinical decision-making in intensive care. He receives equity from MDClone which takes clinical data and produces deidentified versions of it. He receives equity from AESOP which makes software to reduce medication error rates. He receives research funding from IBM Watson Health. WGD has received consultancy fees from Google and Bayer, unrelated to this work. The other others report no conflicts of interests.

Historically, adult congenital patients have longer waitlist time and worse outcomes on the heart transplant waitlist as well as poorer early post-transplant survival. A new heart transplantation allocation system was implemented in the United States on October 18, 2018. The effect of the new allocation system on adult congenital patients is unknown. Adult congenital patients listed for transplantation between November 1, 2015 and September 30, 2019 registered in the United Network for Organ Sharing were included in the study. October 18, 2018 was used as the limit to distribute listed and transplanted patients into old and new groups. A total of 399 patients were listed for heart transplant only, 284 in the old system and 115 in the new system. Clinical characteristics were similar between both groups. The cumulative incidence of poor outcome on the transplant list was similar in both groups (P = .23), but the cumulative incidence of transplant was higher in the new system group (P < .009) and was associated with a shorter waitlist time. The one-year post-transplant outcome was similar between old and new groups (P = .37). The new allocation system has benefited adult congenital patients with increased cumulative frequency of transplantation without worsening short-term survival after transplantation., (© 2020 John Wiley & Sons A/S . Published by John Wiley & Sons Ltd.)

Historically, patients with restrictive (RCM) and hypertrophic cardiomyopathy (HCM) experienced longer wait-times for heart transplant (HT) and increased waitlist mortality. Recently, a new HT allocation system was implemented in the United States. We sought to determine the impact of the new HT system on RCM/HCM patients. Adult patients with RCM/HCM listed for HT between November 2015 and September 2019 were identified from the UNOS database. Patients were stratified into two groups: old system and new system. We identified 872 patients who met inclusion criteria. Of these, 608 and 264 were classified in the old and new system groups, respectively. The time in the waitlist was shorter (25 vs. 54 days, P < .001), with an increased frequency of HT in the new system (74% vs. 68%, P = .024). Patients who were transplanted in the new system had a longer ischemic time, increased use of temporary mechanical circulatory support and mechanical ventilation. There was no difference in posttransplant survival at 9 months (91.1% vs. 88.9%) (p = .4). We conclude that patients with RCM/HCM have benefited from the new HT allocation system, with increased access to HT without affecting short-term posttransplant survival., (© 2020 The American Society of Transplantation and the American Society of Transplant Surgeons.)